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St. John Fisher College Fisher Digital Publications

Sport Management Undergraduate Management Department

Spring 5-1-2014

The Role of a Player Development System in Major League

Kyle Conklin [email protected]

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Recommended Citation Conklin, Kyle, "The Role of a Player Development System in " (2014). Sport Management Undergraduate. Paper 6.

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This document is posted at https://fisherpub.sjfc.edu/sport_undergrad/6 and is brought to you for free and open access by Fisher Digital Publications at St. John Fisher College. For more information, please contact [email protected]. The Role of a Player Development System in Major League Baseball

Abstract This paper looks at the role of a player development system and the possible paths to success in Major League Baseball (MLB). The study looked at rookie players in the MLB to see if the path of their journey to the major leagues has an influence on their success as a ookie.r Two paths were studied, those who played collegiately and those who went through the minor leagues straight from high school. This study used quantitative data to analyze the differences in player’s performance as rookies through statistics such as average and on-base percentage for hitters and winning percentage and earned run average for among other categories. This was used to show the differences in performance of rookies and allow us to see if there is a connection between greater success and previous baseball experience. This study highlighted those issues and topics within the industry including; how sports work, finances, the professional drafts, contributions to player performance, and cognitive development of . Results showed that there was not a significant difference in production between high school and collegiate players during their rookie year. These results suggest that perhaps any sort of organizational philosophy one way or the other may be faulty, and an organization should simply look at the player and not worry so much about their level of experience.

Document Type Undergraduate Project

Professor's Name Dr. Dane-Staples

Keywords , Player Development, Baseball

Subject Categories Sports Management

This undergraduate project is available at Fisher Digital Publications: https://fisherpub.sjfc.edu/sport_undergrad/6 THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 1

The Role of a Player Development System in Major League Baseball:

How does MLB rookie success relate to previous baseball experience?

Kyle P. Conklin

St. John Fisher College

Author Note

Kyle P. Conklin, Department of Sport Management, St. John Fisher College

Correspondence concerning this article should be addressed to Kyle Conklin, Department of

Sport Management, St. John Fisher College, Rochester NY 14618

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 2

Abstract

This paper looks at the role of a player development system and the possible paths to success in

Major League Baseball (MLB). The study looked at rookie players in the MLB to see if the path of their journey to the major leagues has an influence on their success as a rookie. Two paths were studied, those who played collegiately and those who went through the minor leagues straight from high school. This study used quantitative data to analyze the differences in player’s performance as rookies through statistics such as batting average and on-base percentage for hitters and winning percentage and earned run average for pitchers among other categories.

This was used to show the differences in performance of rookies and allow us to see if there is a connection between greater success and previous baseball experience. This study highlighted those issues and topics within the industry including; how minor league sports work, finances, the professional drafts, contributions to player performance, and cognitive development of athletes. Results showed that there was not a significant difference in production between high school and collegiate players during their rookie year. These results suggest that perhaps any sort of organizational philosophy one way or the other may be faulty, and an organization should simply look at the player and not worry so much about their level of experience.

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 3

Introduction

The development of young players is a key to the success of any major league sports franchise. No organization wants to invest time and money into a player who fails to make it to the major leagues. This study explored whether MLB rookie success relates to previous baseball experience. The findings reported in this study will help when it comes to Major League Baseball and the philosophy of an organization when it comes to drafting and developing players within their organization.

Investing time, money, and resources in a player can be very taxing and to have that player fail to make the impact they were expected to do when reaching the major league level can be rough on an organization. With the current league structure the way it is players drafted relatively high are often guaranteed millions in signing bonuses and before they even step on the field (Van Sweep, 2010). If this research being conducted finds that there is one route that is more of a guaranteed success than the other it can be very beneficial to major league organizations. If a small market team relies heavily on their rookie players then they may be more inclined to the more impactful player as opposed to the ones who may take longer to develop in the majors. The research conducted for the literature review of this study will come primarily from the following list of categories; the role and workings of minor league sports, contributions to player’s performance, pro draft rules and protocols cognitive development of a player, and financial management for both a player and team. These topics will span across all of the major in including Major League Baseball, the National

Hockey League (NHL), the National League (NFL), and the National

Association (NBA). The articles written at a scholarly level is very limited when it comes to the impact of player development or minor league sports on the preparedness of an when THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 4 reaching the highest level of in their sport. Most of the research that has been conducted on minor league sports simply focuses on fans and attendance. This study will help shed light on a part of sports that has been for the most part ignored in the scholarly circle.

Statistics were gathered to support this hypothesis by compiling rookie year statistics for both pitchers and position players during first full year in Major League Baseball. The sample that is going to be used will be rookie players who completed that during the 2009, 2010, and 2011 campaigns. The point of this research is to see how influential rookies with either college or high school experience are to their particular organization when it comes to their statistical data in their first year of professional play. The factors that will be looked at in the analysis of this study will be purely statistical. The data that will show the answer to this question are all statistically based and reflect the performance of the athletes in Major League

Baseball.

Literature Review

Role of Minor League Sports

Minor league sports have become a big part of the professional sports landscape in North

America. Its role in getting athletes ready for the pros is something that can be incredibly helpful for an organization and its players. Major League Baseball has developed an extensive minor league program that incorporates player’s right from high school or collegiate institutions

(Winfree, 2005). Though this study will focus on the MLB for its data source the literature review however will focus on the NHL, NFL, and NBA as well.

Major League Baseball, along with the has incorporated minor league sports as a way to develop their prospects and make them into better rookies and young players. However some professional North American sports have decided to go away from this THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 5 development approach and throw their players right into the fire. The does not have any directly affiliated minor league development player. The National Basketball

League primarily follows the NFL’s approach but does have a developmental league known as the D-League. The D-League has made an attempt to strengthen the league by increasing affiliations with NBA teams but still, not even each team has their own minor league affiliate and some D-League teams have up to four NBA affiliations (Lombardo, 2012). However the NBA does not use the D-League as a typical developmental league. Most players drafted into the NBA showing any promise will report directly to the NBA franchise.

The lack of a minor can greatly hurt the development of a player. Not only does a minor league system give them the chance to develop their skills but it gives them an adjustment period to get accustomed to the life and lifestyle that comes with being a professional athlete. Without the acclamation period that the minor leagues provide, rookie athletes in the

NFL and NBA are at a disadvantage. A minor league system also allows for a team to better control player . A league with a player development system allows teams to give smaller signing bonuses and sign their players to minor league contracts. This lowers financial risk while seeing if players can evolve into major league prospects (Broshuis, 2010) Teams with no player development system are often forced to give up very big signing bonuses to early round picks without seeing any performance on the field. This is why Jim Trotter of Sports Illustrated’s name for these players is “Million Dollar Maybes,” (Trotter, 2010).

One important aspect of minor league sports is that it serves as a barometer for predicting future major league production. However even this can be difficult, a study by Longley and

Wong found that future success of major league pitchers is extremely hard to predict based on their minor league statistics (Longley, 2011). They found that through a study of 1200 pitchers THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 6 over a 20 year span that minor league statistics were actually of limited value in predicting major league success (Longley, 2011). This shows how difficult it is for an organization to predict major league success even when looking at minor league statistics, a place where everyone is a professional. This shows that major league production is difficult to predict. So when the NBA and NFL draft players based on college statistics only, it is very risky when predicting future professional success. It is difficult to prove just how talented a player is when there playing against competition where a limited amount even have the talent to play in a professional setting.

An important part of minor league sports in establishing the sense of community. Minor league teams offer members of an organization a chance to bond and form a sense of community with their current and future teammates. A study by Warner and Dixon looked at this potential benefit, and what was most important to athletes in creating this sense of community. These included leadership opportunities, equity in decisions, competition, and social spaces (Warner,

2011). Minor league teams give players these chances where they would not be afforded them in a major league setting. When a player has a chance to develop their leadership skills in the minors it has the potential to translate to a major league team when they reach the pros.

Another benefit of minor league sports is that it allows for low budget teams to compete.

The strategy known as Moneyball in Major League Baseball involves the use of a combination of young talented players with low salaries, mixed with low budget free agents (Gerrard, 2007).

If the NBA and NFL had a development system that incorporated the same pay scales as the

MLB and NHL then low budget teams could develop talent from within and control salaries. It would be a low risk technique that could allow for teams to sustain success (Mason, 2007).

Another major part of a player development system is progression through the levels of the system. A study found that the progression between levels was a direct result of the player’s THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 7 deviation from the mean (Spurr, 1994). This means that if you do well you will move up and the opposite if a player is to struggle. As far as these players moving up the ladder they also get more fan exposure and begin gaining more and more attention from fans. A study found that when top prospects in baseball progress through the system there is a direct increase in fan attendance for their (Gitter, 2011). In this case players can begin developing their star power while their still in the minors and can make a positive impact upon attendance when they arrive in the majors (Braunstein, 2005).

Contributions to Player Performance

Another important factor to look at when helping to show the importance of a player development system is to look at what contributes to player performance. Not only are there factors that influence the performance of player’s on the field but there are also many factors away from the playing field that contribute to the performance of an athlete. One factor that is rarely considered is the impact of professional sports on the amount of sleep a player gets. This may seem like a trivial thing but a lack of sleep can hurt the performance of an athlete and cause a hindrance on the growth and repair, neuro-muscular performance, cognitive functioning, and emotions (Venter, 2012). Young athletes are not use to the grueling schedule that comes with professional sports. This is really a scenario that college sports cannot provide. As a professional athlete you are constantly on the road away from your family, and the minor leagues allow for this adjustment period.

Another factor that contributes to performance on the field is the difficulty of the adaptation process of professional sports. National Hockey League coaches are integrating adaptation teaching techniques into their strategies as a way to attain the best possible performance from their athletes (Battochio, 2010). Coaches and teams have begun educating THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 8 their players on issues including media demands, life style changes, demotion to the minors, transactions, and the sense of belonging and trusting (Battochio, 2010). A psychologically based journal looked at the effect of team member’s trust on a team’s performance. They found that teams with better team cohesion had more success on the field and those who struggled to get along struggled on the field (Mach, 2010). This team cohesion is just one thing that could be built up through a player development system. As far as the actual physical training that is present, MLB trainers tend to look at body composition as the most important parameter (Ebben,

2005). This would be similar for most leagues as the physical fitness of an athlete is highly valued.

A negative issue when it comes to contributions to player performance is the issue of crime and violence among athletes. This has been a prevalent issue is sports and specifically the

NFL. The NFL has instituted a personal conduct policy to help control this violence with harsher penalties for offenders (Janusz, 2012). Another study on this topic argues that the show

“Playmakers” which negatively portrayed football players was actually accurate. They looked at prevalence of injury on the field, steroid use, painkiller use, drug use and domestic violence in the sport and found all of these to be prevalent in the NFL (Fogel, 2012). Another study found that there is often a lot of pressure on young athletes to engage in risky behavior (Diehl, 2012).

Often when a rookie comes into a lot of money these pressures are even more prevalent and have the ability to derail a young athletes career. These behaviors can take away from the performance of an athlete on the field, hurting their off the field lives, and portraying the league in a negative way (Diehl, 2012).

An important factor that organizations need to keep in mind when developing players is their own minor league coaches and their coaching philosophies. A study from the International THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 9

Journal of Coaching Science looked at coaches and athletes perceptions of athlete performance.

The results found that athlete’s perceptions of performance were not always associated with ’s satisfaction with performance (Lorimer, 2011). This study is significant because it shows that sometimes coaches and athletes have different ideas of success. Meaning that if a player was just thrown into the pros not only do they miss out on further coaching but they may not jell with the professional coach and it could hurt their development and the teams performance. This study showed that it is very important that a coaching philosophy instilled at the major league level is stressed throughout your development program to develop players who fit the mold and goals of your organization.

Professional Draft

One important step in understanding the impact of player development is interpreting how the professional drafts in these leagues work. One interesting aspect to look at is the rules that certain leagues have put into place. The NHL and MLB do not mandate that the player attends college, where the NBA and the NFL do by issuing their age requirements. There are many legal issues that revolve around a player forgoing their amateur status to turn professional.

These can include factors such as the hiring of agents and advisors, extra eligibility, player injuries, and undrafted players (Levy, 2012). An article from the Case Western Reserve Law

Review questions whether the placing of an age restriction on entry is actually legal (McCann,

2006). This is an interesting thought because the two leagues that don’t use an age limit are the ones who have a strong player development system. It bring into question whether or not the

NBA and NFL really just implement this restriction as a way to have a free player development system in the NCAA. It is important to note that the NBA used to have no such age limit. The

Seton Hall Journal of Sport Law argues that this restriction isn’t actually necessary and points THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 10

out how athletes such as made the jump and turned into all-star players (Rosner,

1998). The articles importance lies in how it points out successful players made the jump from

high school and were impactful. It shows that maybe the clearly most talented players don’t need

a player development system or college experience.

Another study performed in the International Journal of Sport Finance looked at the

ability to predict NBA success based on college production. The study found that college

basketball only had some significance when predicting a NBA career (Coates, 2010). When you

take this fact into effect and the fact that the NBA has just two rounds in its professional draft, it

means that a significant amount of players may have been overlooked and not given the shot to

prove themselves as an NBA player. If the NBA would implement stronger connections with

their development system they could increase the rounds of the draft and work on developing

more players with potential.

Going along these lines the Journal of Sport Behavior looked at whether or not draft

position of a player was a good indicator of NHL success. They however found that draft

position was actually a poor indicator of NHL performance (Voyer, 1998). This shows that often

player evaluators make mistakes and these late round picks only make in to the majors through

proving themselves in the minors. Without such an opportunity in the NBA or NFL there is a

very good chance that many player’s with professional potential have been overlooked and never

given a chance to prove themselves.

An article by Deubert and Wong describes the evolution of the signing bonus in the NFL and the prevalence of guaranteed money. The authors describe how originally the signing bonus was just a small incentive for the player to sign a contract with a club, but it has now turned into a significant amount of guaranteed money (Deubert, 2009). When a player is guaranteed large THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 11

sums of money it puts the organization in a financial risk. When they guarantee this money there

is no way of recouping the money even if the player doesn’t pan out to their potential. If the

leagues instead had the ability to send the player to the minors they could see if the player

actually is worth the potential long-term investment.

Another study conducted in 2006 looked at the ability of off the ice performance tests to

predict on ice success. The study found that at least in the NHL off ice tests are not accurate

predictors of the athletes overall skill in a setting (Vescovi, 2006). This is not only

important for hockey but all sports, especially the NFL and their pre-draft combine. Based on

these finding the combine would be of little to no significance in predicting the players on field

ability. Another important factor is to look at how draft order affects players playing time at the

professional level. A study completed about this situation in the NBA found that teams are more

likely to hold onto a player who was drafted early on over a player who is actually more

productive just because of the money they have invested in them (Staw, 1995). This study points

out a huge flaw in the NBA’s system. When teams keep a highly drafted player over a more

productive one just because they have invested so much money in them, is a serious problem. If the NBA were to work more closely with the D-League and control salaries than there would not be this obligation to keep these unproductive high draft picks.

Cognitive Development

Another important factor to take into account when looking at the benefits of a player

development system is its impact on a player’s cognitive development. With drafted players

being sent to minor leagues they have the benefit of developing as not only a player but as a

person without the pressures to perform at a major league level. A study performed in the Journal

of Personality found that significant mental development occurs between the ages of 17 and 27 THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 12

(Donnellan, 2007). When a player is selected to any of the professional drafts they are at the lower level of this continuum, meaning they have really just begun the journey of emotional and mental maturity. It has also been found that emotional maturity has a significant impact on the level on the player’s performance. A study done in the International Journal of Sport & Society looked at the impact of emotional maturity of professional hand ball players. This study used a test that looked at five subscales including emotional instability, emotional regression, social maladjustment, personality disintegration, and lack of independence. The study concluded that the international level players, the most talented, also had the highest emotional maturity

(Rathee, 2011). This is extremely significant because it shows that those athletes with the most emotional maturity have the most success on the field. The minor league opportunity would give these athletes a chance to grow and mature

Another study performed by the University of California found that people develop further cognitively, the more they are exposed to cultural contributors (Gauvain, 2011). This helps to reinforce the value of a player being exposed to the challenges and hurdles of life when they are still young playing in a minor league setting. When you select a player for instance in the NBA, the player has most likely gone from living with their family to usually only one or two years in college, a very controlled environment. The minor league system gives players the opportunity to get out on their own and feel what it is like to take on some further responsibility and have to make their own decisions. Something as simple as renting an apartment and having to pay your own bills can go far in the emotional maturity process of an athlete. On the contrary a study by the Change journal found that when a young adult goes to college they also experience significant cognitive development as part of their intellectual learning (Baxter

Magolda, 2006). This proves that there are benefits to an athlete attending a university. Though it THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 13

may be a different approach, it still leads to increased cognitive development which in return

leads to better performance on the field.

An issue when it comes to cognitive development is diagnosing emotional and mental

disorders in athletes. An article from the Journal of Clinical Sport Psychology discusses the

diagnosing of emotional disorders in athletes (Ronald, 2008). One way of combating this is by

having a specialist in diagnosing emotional disorders, this can increase the diagnostic and

treatment abilities of an organizations team. Mental issues that have been

prevelant in sport include; anxiety and mood disorders, eating disorders, substance use, and ADD

(Ronald, 2008). This was really brought to light this previous NBA season with Houston Rockets

player Royce White. White is the first prospect to freely admit he suffers from anxiety (Torre,

2012). Unfortunately White and the Rockets have struggled to deal with the situation and White has not played this season as a result. This shows that clearly this player wasn’t ready for a major league setting, perhaps if the Rockets had eased him into the situation through a player development system it could have worked out. Also the Rockets took a big financial risk signing

White and as a result have had no return on their investment.

Some experts say that the NCAA should make more of a conscious effort to educate division one athletes on the professional sports road (Wong, 2011). For many division one athletes the goal is to make it into professional sports, and realistically that is happening for many major sports programs. Most parents and students are uneducated in this process and some feel the NCAA needs to step in and take urgent action to help protect and educate young athletes

(Wong, 2011). Unfortunately or not, for many division one athletes it’s not primarily about the education and though the NCAA may not be happy about it, perhaps they need to start acknowledging that this is the role they have become for many athletes. THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 14

Financial Management

One of the most important parts in the development of a young athlete is financial management. This is equally significant for both the player themself and the teams that are paying out this money. From the perspective of the organization the signing of a player is an extremely risky financial endeavor (Kedar-Levy, 2008). This is obviously risky because players are so highly paid. When compared to individual athletes who compete as one, team based athletes make significantly more money (Hilpirt, 2007).

The Review of Financial Studies found that the use of signing bonuses as an incentive has become very prevalent in major league organizations (Van Sweep, 2010). This is a dangerous recruiting tool because these bonuses are typically guaranteed money. This is just that much more risk that is being put on these organizations. A study focusing on the financial management strategies of organizations found that in Major League Baseball the best way to be successful and control spending is to establish a strong player development system and win from within (Chen, 2008). For organizations that choose to follow this model it is very important for them to get a return on their investment. These organizations rely on their rookie players to make a significant impact and need strong production in a player’s first year.

Perhaps the greatest impact of financial management in this study is on the ability of the players themselves to manage their finances. Just as the athletes sport is a team effort so is the management of their money (Dowell, 2011). Any athlete who makes a significant amount of money should have a team in place for any situation that may come about regarding their financial situation. According the study by Dowell an athlete should put together a team made up of an agent, an accountant, an attorney, an insurance professional and a wealth expert. An accountant can be especially important when it comes to issues like the “Jock Tax.” The jock tax THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 15

is essentially a tax that states employ on professional athletes for doing work in their state. This

means athletes have to pay a tax in any state they play in during the season even outside of their

state of residence (Shaheen, 2012). This is influential because a lot of athletes don’t realize that a

million dollar signing bonus doesn’t mean they actually get a million dollars. If rookies were

more educated on this process they could better prepare financially.

Professional athletes are often tempted by the athlete lifestyle. Often players take that

first paycheck and simply see the dollar signs. It is the of this wealth management team to

make sure the athlete stays on track and spends within their means and makes smart investments.

A study by Reinhold looks at some of the differences in the financial situations between athletes

and the regular individual. The study found that the average person will work for 35 to 45 years

and make between $1.5 and $3.5 million. Where an athlete will play for an average of 7 to 12

years and make between $5 and $25 million, however their career will be over before age 40

(Reinhold, 2000). The problem many athletes face who have the short professional careers is that

they don’t understand that this lifestyle is not sustainable, and that is where a financial planner

needs to be working with a player to make sure their money can last. A financial planner who

works with a major financial management firm states that when he first sits with a client

after they get their first contract, he plans accordingly assuming this is the only contract they will

ever get in their career (Jackson, 2013). Though players don’t like to hear this, this is a

philosophy that needs to be taken. Sports are unpredictable and you never know if that next pay check will come.

Financial David Neumann points out how a common misconception is that people believe athletes retire at the same point as everyone else (Neumann, 1988). Typically when a normal person invests their earnings for retirement they begin to use the money at age 55, THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 16 however with an athlete they begin using their savings usually by their mid to late 30’s. This can also be a difficult transition for athletes to have something they have been doing their entire lives to suddenly be gone. Often athletes look to invest their money in another venture and that is where a financial manager comes in to make sure that if they do it is a smart investment

(Neumann, 1988). Finances and big money contracts are extremely risky for both teams and players and is something that shouldn’t be taken lightly in professional sports.

Methods Research Tradition

A post-positivist approach was used in this study. A post-positivist paradigm acknowledges that fixing meaning(s) is not a neutral act, and that the questions raised reflect particular interests (Henderson, 2011). In this approach the researcher has some influence on the findings. In this case the influence comes in the sample being selected. The criteria for selection was made at the researcher’s discretion. There was no central group to look at, the group was chosen based on criteria best believed to fit this study.

Also this research was conducted using quantitative approaches, and much of the contribution to this work was in the realm of research design and statistical analyses.

Quantitative studies use sophisticated modeling procedures to demonstrate support for the sequential links in the chain of events (Horn, 2011). In this study this chain of events represents the possible path in levels of baseball participation. This research tested to see if there is in fact a sequential link that allows for rookie baseball success to be predicted based on past baseball experience.

A quantitative research design allows flexibility in the treatment of data, in terms of comparative analyses, statistical analyses, and repeatability of data collection in order to verify reliability (Jones, 1997). Quantitative methodologies allow for comparison and replication. This THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 17 is important when it comes to the repeatability of the study and the ability to build upon the findings. As this study only encompasses one three year study by taking this approach someone could easily choose a different three year period to test the validity of the result.

Conceptual Framework

This framework outlines the variables, intervening variables, sample, and procedure that took place in this study. This study looks at a number of different factors and variables that contribute to the success of rookie players. After data was gathered and placed into a spread sheet, a logistical regression was used to help interpret results and determine the predictive ability of the results.

Variables

Multiple variables were present in the study. These were addressed to clarify the results and make the study as accurate as possible.

College/High School

o This serves as the primary dependent variable for this study. The athletes were

broken down by college and high school to determine if one particular path leads

to the most rookie success.

Number of months in minors

o This was a key determining variable in the study. Time is one of the most accurate

predictors of the impact of the minor leagues. It was expected that time would be

a large contributor when comparing the paths of college and high school players.

o Time was measured by the number of days the player spent in the minor leagues.

The number of months the player stayed in the minors was broken down into

numerical form to be imputed into SPSS. For example if a player spent four THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 18

months in the minor assuming 30 days per month, this players time would be

imputed as 120 days of minor league service.

Number of at bats / innings pitched

o This will show the amount of playing time a certain player had while in the

minors. It may be a more accurate predictor as opposed to time. A player may

spend significant time while getting few appearances, or progress to the majors in

a short amount of time as a result of playing every single game.

Offensive statistics

o Batting Average (AVG), At Bats Per (AB/HR), At Bats Per Run

Batted In (AB/RBI), On Base Percentage (OBP).

o Qualification (Qualified year to date) – In order to qualify for batting titles in

averaged categories, a player must average at least 3.1 plate appearances for every

game his team played. Sorting by qualified year to date excludes all player not

currently on pace to reach that minimum. (MLB Miscellaneous Rules, 2013)

Pitching statistics

o Winning Percentage (W%), Earned Run Average (ERA), Walks Per Nine Innings

Pitched (BB/9), Strike Outs Per Nine Innings Pitched (SO/9), Walks Plus Hits Per

Inning Pitched (WHIP).

o Qualification (Qualified year to date) – In order to qualify for pitching titles in

averaged categories, a player must average at least one inning pitched for every

game his team has played. Sorting by qualified year to date excludes all players

not currently on pace to reach that minimum. (MLB Miscellaneous Rules, 2013)

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 19

Intervening variables

There were multiple intervening variables present in this study. Some prospects spend very little time in the minors and have great success at the major league level, for example Bryce

Harper, Yasiel Puig, and Jose Fernandez who spent very little time in the minors and became

MLB all-stars their first year. This could disprove the time element as a variable to major league success. This type of player would however be present in the study if they met the qualifications presented. Though they could possibly skew results these players cannot be omitted because of their talent. There is also a possibility of an immeasurable x-factor, if there is some intrinsic quality that is possessed by certain athletes that cannot be taught or coached. In this case it would be considered a limitation to the study. These intangible variables may be more of a contribution for some players but can’t be measured.

There are some aspects of a players influence and impact that cannot be measured through statistical data. Some of the impact to a team can come from immeasurable statistics such as leadership. This was considered a limitation to the study.

Players from overseas or other leagues will not be included in this study. If someone played independent league baseball or played professionally in another country (Japan, China,

Cuba) there is a good chance that they will be a rookie who has spent no time in the minor leagues. This was taken into account when looking at the sample.

Foreign players will be limited in this study. Any player who was drafted out of another country will be eliminated from the study. As these players do not participate in high school sports it would not follow within the constraints of the study. Since many foreign players participate in academies and clinics only and do not play high school or college baseball it would not align with the goals of the study. This much of a focus on baseball only would put them at a THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 20 competitive advantage over other players who have to balance baseball with school work or other off field endeavors.

Defensive statistics did not play a role simply because of the difficulty in measuring . The only defensive statistic currently measured in traditional is errors which is not an accurate enough measurement of total defense. There is really no way to statistically measure arm strength or fielding range, two things which set some players apart from others on the defensive side of the ball.

Stratified random sampling

For this study only rookies were studied. The official determining status of a rookie according to Major League Baseball is as followed; A player shall be considered a rookie unless, during a previous season or seasons, he has (a) exceeded 130 at-bats or 50 innings pitched in the Major Leagues or (b) accumulated more than 45 days on the active roster of a Major League club or clubs during the period of 25-player limit (excluding time in the military service and time on the disabled list) (MLB Miscellaneous Rules, 2013). By using the league with the (DH) we can eliminate a possible intervening variable when it comes to rookie starting pitchers. As starting pitchers do not have to hit it allows for more pure pitching stats since pitchers will not need to spend their time worrying about hitting or face the risk of injury. Also since there is a DH, other rookie position players will be eligible to look at that either DH or spend some time as the DH and therefore have resulted in a larger sample to study. The study was not a completely random sample because there were certain qualifications that needed to be met to take part in the study. If a completely random sample was taken from the rookie class we would wind up with a player hitting .300 but he only played in the minimum required amount of games. This would not be an accurate representation on the ability of a THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 21 player. That is why the minimum statistics to qualify for official MLB statistics explained earlier were taken out of the question. The qualifications that are listed above would create a sample with a large amount of variance between playing time and could bring inaccurate results. Also the regular season statistics will only be taken into account in this study. Additional games played in the post season would skew the results as certain rookies would gather more at bats due to their team’s participation in the playoffs.

This study looked at players from the 2009, 2010, 2011 seasons. These seasons were selected as they are the three leading up to the latest collective bargaining agreement (CBA) in the MLB (DeSchriver, 2012). The most recent CBA was enacted after the 2011 season so any recent rule changes would have been put into place after the 2011 season (DeSchriver, 2012). A significant sample size requires three seasons of players so the previous three seasons were selected as a result.

The players chosen met the playing time criteria that had been put together for this study.

All batters selected had a minimum of 275 at bats. This is roughly half of the at bats a typical everyday player would get during a season. This allowed for a significant number of players to be chosen while still having a strong impact on their team during the season. Pitchers who have been selected for the study have a minimum of 100 innings pitched in their respected season. 100 innings is slightly under half of the innings pitched by the pitchers with the most innings pitched during these seasons. This is the highest number of innings pitched that could be studied while still having a significant number of participants. When these qualifications were applied to the three year sample size for both pitchers and hitters it resulted in a total sample of 48 players, 22 pitchers and 26 hitters.

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 22

Procedure

Data collection began by breaking down the players in the three year time period into pitchers and position players. Player’s statistics were then inputted into SPSS to categorize their statistics. Categories for both pitchers and position players included the dependent variable college or high school first, total games played and days spent in minors. Position player only statistics also included; at bats, batting average, on base percentage, at bats per home run, and at bats per run batted in. Pitching statistics included; innings pitched, winning percentage, earned run average, walks per nine innings pitched, strike outs per nine innings pitched, and WHIP. All of this data was obtained through the websites Baseball Reference and Baseball Almanac. When it came to breaking down the data the statistics were tabulated by the Statmaster program on the

Baseball Almanac website. Descriptive statistics were primarily used to decipher the data. Mean was an accurate ways to see the results of the study and easily compared between multiple categories. Once descriptive statistics were gathered and tabulated we were able to see if there was a clear difference in rookie year production between college and high school players and also if time spent in the minor leagues did play a significant role in player performance.

A logistical regression was used to look at determining factors in this study. This type of regression allows for the predicting of outcomes based on one or more dependent variable

(Gratton, 2010). This study was able to show the strength of relationships and if there was a correlation between the two variables which were in this case, the impact of college or high school on their success as a rookie. This analysis was able to show if there was any predictive ability in model. If there is a strong enough correlation the model will have the ability to trace the rookie stats back to previous experience which in this case is either high school or college baseball participation. THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 23

Results

After looking at the data collected from the collegiate and high school players there was little difference between choosing players from one path or the other. The data showed there was not a clear difference between high school and college athlete performance as rookies for both the hitting and pitching categories. Also after running a logistical regression of the data there was not significance in the finding. As a result of the regression analysis there is a lack of correlation between the statistics and their ability to predict high school or college participation. For a detailed description refer to appendix C1 and C2.

Whether it was the hitters or the pitchers there was not a large disparity between the two sides in the statistical categories that were measured. In the pitching categories both the high school and college pitchers displayed similar results. When earned run average (ERA) was tabulated the high schools mean of 4.36 surpassed the 4.86 mean ERA of the collegiate pitchers.

High school pitchers also held an advantage when it came to WHIP. High school pitchers posted a WHIP of 1.43 compared to the 1.45 of the collegiate pitchers. The collegiate pitchers finished with a mean winning percentage of .543 compared to the high school pitchers who on average failed to win the majority of their starts with a .468 winning percentage. This statistic however could be influenced by the overall performance of their respected teams. College pitchers also averaged more strike outs per nine innings pitched, averaging 6.08 compared to the 5.64 by the high school side. College pitchers led as well in walks per innings pitched allowing 3.46 in comparison to the high schools 3.48.

Hitters from high school and college also showed similar results in the statistical categories that were measured. The college hitter’s batting average of .261 was slightly ahead of the .260 mean average of the group of high school hitters. The on base percentage category was THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 24

also on average higher for college batters with a percentage of .326, in comparison to the .317 of

the high school batters. College hitters were also more productive when it came to driving in

runs, average an RBI once every 9.00 at bats compared to the 9.68 at bats in took for the

comparable high school hitters. High school hitters lead the collegiate when it came to AB/HR

hitting a home run once every 51.05 at bats compared to the college hitters one every 63.95 at

bats. Worth noting when it came to this particular statistic one high school player failed to hit

any home runs during his rookie season. As a result this player was removed from the group

when the statistic was tabulated.

Other categories that were tabulated for both hitters and pitchers included; games played

during the rookie season, at bats during the season, total inning pitched during rookie season, and

the total number of days that the players spent in the minor leagues prior to completing their

rookie season in the major leagues. These averaged results can be seen in table A3 and A4.

The statistical analysis results of the rookie hitter category will be discussed first. When

the Omnibus tests of model coefficients were applied to the rookie hitters a significance level of

.587 resulted showing a lack of predictive value in the present model. A Nagelkerge r square

model resulted in a figure of .139 or only a 13.9% ability to explain the high school versus

college path to the major leagues. Rookie hitting statistics showed a 57.7% predictive ability

before the statistical categories were applied, after the application of the statistics high school

versus college showed a predictive ability of 61.5%. Though still not statistically significant,

there was a resulting increase of 3.7% in the predictive ability of the study after these particular

statistics were introduced. Statistical significance did result when it came to hitters and their time

spent in the minor leagues. The Pearson correlation resulted in findings of , r = -.618, p (two tailed) < .01, showing a negative correlation between time spent in the minor leagues and college THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 25

participation. As a result a correlation between less time spent in the minors for collegiate

pitchers and more time spent for the high school only athletes presented and confirmed the

predictive ability of the statistic. Complete data results for hitters can be seen in appendix C1.

For pitchers the Omnibus tests of model coefficients showed a significance level of .003

showing some significance in the predictive value of the model. The Nagelkerke r square model

resulted in a value of .741 showing the models ability to explain 74.1% of the high school and

college paths. The Hosmer and Lemeshow test showed a significance level of .781 showing good

predictive abilities of the model. For the pitchers the original predictive model of the study was

50% before the application of the statistics. After the application of the statistics the resulting

predictive ability of the model rose to 81.8% and overall increase of 31.8%. Though no

individual baseball statistic was significant on its own, as a collective group of statistics they

showed to have good significance when it comes to predictive ability. When it came to time

spent in the minor leagues there was significance between time spent in the minors and their

career path. A Pearson correlation showed, r = -.492, p (two tailed) < .05. Both of these models showed that spending more times in the minor leagues is negatively correlated with college attendance, resulting in a significant correlation between days spent in the minor leagues and their participation in either college or high school baseball only. Full statistical data results for pitchers can be seen in appendix C2.

Discussion

The results of this study showed that there was not a clear difference between the impact of high school only players and college players in their rookie year production. Statistics and analysis showed that there were no clear predictive abilities for hitters or pitchers. Though for pitchers some of their statistics were close to gaining some significance in their predictive value, THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 26 such as winning percentage, but overall not enough to make a clear definitive statement on their impact and predictive abilities. Statistical analysis did show that there is a relationship between the path of a player based on their time spent in the minor leagues.

The result of this study helped to reinforce the role of minor league sports and its ability to prepare players to play at the highest level. Though some people may be on the side of college and the experience it has to offer, and others may agree with players leaving right of high school to turn professional the results showed that players are essentially equally prepared when coming out of the minor leagues. The findings helped to reinforce elements of the literature review including; cognitive development, the contributing factors to player performance, and the overall role of minor league sports. The fact that the two groups were so equally productive when they arrived in the major leagues shows that in either case the minor leagues is sufficiently preparing player’s if they either spent significant time out of high school or a shorter time for the college players. These results show that athletes are developing equally in the careers and on and off the field and as a result are contributing equally to their teams at the major league level.

Though this study encompassed and found what it set out to do, there were several limitations that presented themselves throughout the study. One example being that this study only encompassed one, three year period of rookies. To further validate the findings it would be necessary to run the same statistics with multiple groups of players from different time periods.

Also for this study only the American league rookies were studied, if the rookies had been included it could have affected the results of the study. Another limitation that was present is the fact that the defensive ability of players was not taken into account. Since the only statistical category for defense is errors, which is really not a very accurate assessment of a THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 27 player’s defensive ability, defense was left out of the study for its lack of measurability. A limitation presented itself in the amount of statistics and what statistics were looked at in this study. Due to limitations this study used the basic, historically relevant baseball statistics. If more statistics were looked at or possibly if new sabermetric statistics were introduced to the study it would be hypothesized that the study would only continue to reach to a significant correlation between the two sides. As the statistics were introduced into this study it became more accurate, with the predictive capacity of the model increasing 3.7% for hitters and 31.8% for pitchers. It would only make sense that if the number and scope of statistics were increased the predictive capacities would do the same.

One piece of significant data that was present for both the hitters and pitchers studied was the difference in amount of time spent in the minor leagues. As the results showed, there was significance in the data collected when it came to predicting a players path based on time spent in the minor leagues. College hitters averaged 391 days spent in the minor leagues before their promotion to the majors. That is compared to the 689 days spent in the minors by high school hitters. Some executives may be swayed by the younger high school player when it comes down to a decision between them or the collegiate hitter. However when you average out the time spent in the minor leagues developing the arrival age to the major leagues is not all that different.

If you take into account the fact that the minor league season runs from roughly the beginning of

April to the end of August that is about five months of playing time. If you average thirty days per month for five months that equates to 150 days of playing time per season. For collegiate hitters, when you divide that into their average days spent in the minors you get on average a player who spends 2.6 seasons in the minor leagues. This is compared to the high school hitter who on average will spend 4.6 seasons in the minor leagues. Similar results were seen when THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 28

college and high school pitchers time spent in the minors was looked at. High school pitchers on average spent 476 days in the minor leagues compared to the 287 by collegiate pitchers. When the number of seasons are averaged out high school pitchers on average spent 3.2 seasons in the

minors while collegiate pitchers spent 1.9 seasons in the minor leagues. Since college players

have to stay at school for three seasons there is really only a one year difference between college

and high school hitter’s arrival in the major leagues and less than two years for college pitchers.

This could be interpreted a couple different ways depending on the organization philosophy of

the team. If a team tended to lean toward the high school player because of the age factor maybe

would take a step back and reconsider if a year to a year and a half in age difference is really

worth taking one player over another. Or if one organization tended to stay away from the high

school players because of the extra time they have to spend in the minor leagues perhaps they

would reconsider because though they have to wait a longer time to see them make it to the

majors, in the end they are still younger than the comparable collegiate when they arrive in the

big leagues.

Though there was not a clear difference between success for high school and college

players these finding would serve useful for teams that may have thought differently and tend to

select one type over the other when it comes to the draft. If a front office saw the results of this

study, perhaps next time it comes down to two players they won’t simply take a player out of

high school for example and take the player who really fits their system and philosophy the best.

These finding would also be very beneficial to the athlete themselves when it comes to

their decision to leave high school for minor league ball or accept their scholarship to a college

baseball program. These results could give them a peace of mind when it comes to making their

decision. Since the data shows that the range between high school and college players making it THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 29 to the majors is just roughly a year difference for position players and about a year and a half for pitchers they can make the decision that’s best for them without worrying solely about baseball.

Not every high school age player is ready to live on their own and go through the daily grind of the minor leagues. The data would suggest that if they are more comfortable with the college route then it will really only delay their arrival to the majors a year to a year and a half. Some players may be ready to make the jump into adulthood and go right to the minors and this will give them a slight advantage when it comes to arrival in the majors, but for those who choose college it can give them the chance to develop both cognitively and physically without the pressures of professional baseball.

Conclusion

Though there was not a large discrepancy between the final mean statistics for the dependent variable for both pitchers and hitters there were still meaningful results. Overall the study did answer the question of how does rookie success relate to previous baseball experience?

Though there was not a definitive result to one side or the other for both categories this is still a significant result. The fact that there was no strong difference in production for either hitters or pitchers shows that both sides no matter the path are equally prepared when reaching the major league level.

As shown by the results we can conclude that either path is equally effective in preparing players for the majors. We can see that playing in college for three years and playing in the minors for a short period of time is statistically similar to going straight from high school to the minors and spending a longer time in the minor leagues. Theoretically this would validate either paths ability to prepare players both on and off the field. It also reinforces the role of the player development system in Major League Baseball. No matter what path these players take to THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 30 professional baseball the MLB has put in place a system that equally and effectively prepares each player to be successful rookies in the major leagues. Strength of this study lies in its repeatability and room for expansion. Though the results lacked statistical significance they did show as more baseball statistics were added into the study into continued to gain more and more significance. If someone were to choose to expand the scope of the target groups and statistics looked at, perhaps significant predictors can be achieved. Overall this study has provided a strong foundation for future research on player development to be based upon.

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 31

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Appendix

Table A1

Hitters AVG. OBP AB/HR AB/RBI

College .261 .326 63.95 9.0

High School .260 .317 51.05 9.68

Table A2

Pitchers ERA W% BB/9 SO/9 WHIP

College 4.86 .543 3.46 6.08 1.45

High School 4.36 .468 3.48 5.64 1.43

Table A3

Hitters Total Games Played At Bats Days in Minors

College 105.6 364.27 391.47

High School 108.0 388.18 688.82

Table A4

Pitchers Total Games Played Innings Pitched Days in Minors

College 27.18 138.02 286.73

High School 26.64 151.36 475.56 THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 37

Appendix B

Original Data Sets

Hitters

Player College/HS Season Days In Games AB AVG. OBP HR RBI AB/HR AB/RBI Minors GB College 2009 69 103 378 0.270 0.347 14 63 27 6 CG College 2009 517 107 375 0.261 0.324 2 31 187.5 12.1 NR College 2009 569 104 358 0.279 0.365 15 45 23.9 8 MW College 2009 192 96 354 0.288 0.340 9 43 39.3 8.2 MM College 2009 783 127 341 0.243 0.333 3 31 113.7 11 AJ HS 2010 642 151 618 0.293 0.345 4 41 154.5 15.1 BB College 2010 522 133 464 0.256 0.320 14 67 33.1 6.9 AA College 2010 186 104 294 0.228 0.316 7 31 42 9.5 MS HS 2010 640 100 289 0.211 0.295 10 33 28.9 8.8 JS College 2010 166 100 348 0.218 0.307 13 48 26.8 7.3 JJ HS 2010 784 109 339 0.263 0.372 5 44 67.8 7.7 RB HS 2010 730 113 301 0.256 0.307 8 45 37.6 6.7 DV College 2010 522 85 299 0.311 0.351 7 40 42.7 7.5 MB HS 2010 760 72 297 0.246 0.296 3 22 99 13.5 JD College 2010 550 88 296 0.253 0.312 4 24 74 12.3 MT HS 2011 813 149 539 0.254 0.291 29 87 18.6 6.2 EH HS 2011 319 128 523 0.293 0.334 19 78 27.5 6.7 MM HS 2011 500 89 338 0.263 0.309 5 30 67.6 11.3 BR HS 2011 521 117 450 0.267 0.310 0 30 0 15 TP HS 2011 885 81 286 0.238 0.305 8 31 35.8 9.2 JA College 2011 509 129 443 0.219 0.282 23 78 19.3 5.7 ET College 2011 378 95 362 0.262 0.313 12 37 30.2 9.8 BM College 2011 361 126 413 0.245 0.287 10 41 41.3 10.1 JW College 2011 337 97 406 0.303 0.340 2 36 203 11.3 DA College 2011 211 90 333 0.273 0.348 6 36 55.5 9.3 MC HS 2011 983 79 290 0.276 0.326 12 46 24.2 6.3

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 38

Pitchers

Player College Season Days In Games IP ERA W% W L BB BB/9 SO SO/9 WHIP /HS Minors JN College 2009 334 31 180.2 3.94 0.684 13 6 59 2.94 125 6.23 1.35 DP College 2009 121 23 128.1 4.42 0.588 10 7 54 3.79 102 7.15 1.35 TC HS 2009 229 32 178.2 4.63 0.435 10 13 72 3.63 90 4.53 1.44 BA HS 2009 275 30 175.1 4.06 0.500 11 11 45 2.31 150 7.70 1.28 RR College 2009 400 29 178.0 4.30 0.591 13 9 79 3.99 141 7.13 1.52 SR College 2009 197 27 138.2 5.52 0.421 8 11 59 3.83 117 7.59 1.49 RP HS 2009 144 31 170.2 3.96 0.609 14 9 52 2.74 89 4.69 1.34 DH College 2009 208 33 138.1 6.12 0.381 8 13 47 3.06 107 6.96 1.50 TH College 2009 246 19 112.0 4.10 0.600 9 6 33 2.65 64 5.14 1.30 DH College 2009 247 23 128.1 5.61 0.579 11 8 41 2.88 65 4.56 1.56 JB College 2009 366 24 119.2 6.54 0.333 6 12 44 3.31 66 4.96 1.74 BB HS 2009 485 19 123.1 3.43 0.583 7 5 32 2.34 65 4.74 1.28 DH HS 2009 561 20 101.1 5.42 0.286 4 10 46 4.09 68 6.04 1.62 MP College 2009 630 40 121.1 3.93 0.846 11 2 55 4.08 69 5.12 1.32 BM College 2010 100 32 175.2 4.30 0.455 10 12 63 3.23 143 7.33 1.34 JA College 2010 305 18 100.1 4.66 0.500 6 6 48 4.31 52 4.66 1.53 WD HS 2010 685 29 168.0 4.07 0.545 12 10 62 3.32 113 6.05 1.35 MT HS 2010 801 28 159.1 4.41 0.435 10 13 69 3.90 88 4.97 1.49 JH HS 2011 601 29 189.0 2.95 0.565 13 10 72 3.43 117 5.57 1.15 ZB HS 2011 562 28 154.1 4.61 0.500 11 11 62 3.62 97 5.66 1.45 TC HS 2011 450 27 142.0 4.75 0.353 6 11 71 4.50 74 4.69 1.67 DD HS 2011 438 20 105.1 5.64 0.333 4 8 54 4.36 87 7.43 1.61

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 39

Appendix C1

Hitters

Logistic Regression

Classification Table

Observed Predicted

HS/College Percentage

HS College Correct Ste HS/College HS 0 11 .0 p 0 College 0 15 100.0 Overall Percentage 57.7

Omnibus Tests of Model Coefficients Chi-square df Sig. Step Step 2.829 4 .587 1 Block 2.829 4 .587 Model 2.829 4 .587

Classification Table

Observed Predicted

HS/College Percentage

HS College Correct Step HS/College HS 4 7 36.4 1 Colleg 3 12 80.0 e Overall Percentage 61.5

Hitters Variable B Sig. AVG -18.748 .435 OBP 23.472 .386 ABHR .012 .332 ABRBI -.209 .340 Constant -1.114 .866 R2 .139

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 40

Hosmer and Lemeshow Test Step Chi-square df Sig. 1 13.951 7 .052

Appendix C2 Pitchers

Logistic Regression

Classification Table

Observed Predicted

HS/College Percentage

HS College Correct Step HS/College HS 0 11 .0 0 College 0 11 100.0 Overall Percentage 50.0

Omnibus Tests of Model Coefficients Chi-square df Sig. Ste Step 17.845 5 .003 p 1 Block 17.845 5 .003 Model 17.845 5 .003

Hosmer and Lemeshow Test Step Chi-square df Sig. 1 4.779 8 .781

Classification Table

Observed Predicted

HS College Percentage

HS College Correct Step HS HS 9 2 81.8 1 College College 2 9 81.8 Overall Percentage 81.8

THE ROLE OF A PLAYER DEVELOPMENT SYSTEM 41

Variables in the Equation Variable B Sig. ERA 7.275 .169 WPercentage 41.111 .064 BB9 1.766 .461 SO9 .550 .468 WHIP -17.462 .502 Constant -38.168 .085

R2 .741